Running MPI Applications

On Fram and Saga users have access to two MPI implementations:

OpenMPI is provided by the foss - and iomkl toolchains; and may also
be loaded directly. For available versions, type module avail
OpenMPI/(note the slash). Normal way of loading is through the
foss-toolchain module, e.g. module load foss/2018a

Intel MPI environment is provided by the intel-toolchain and may
also be loaded directly. For available versions, type module avail
impi/. Normal way of loading is through the intel-toolchain
module, e.g. module load intel/2018a

Also note that quite a few scientific packages is set up in such a
way that all necessary software are loaded as a part of the software
module in question. Do not load toolchains and/or mpi modules
explicitely unless absolutely sure of the need for it!!!

Slurm is used as the queue system, and the native
way to start MPI applications with Slurm is to use the
srun command. On the other
hand, both MPI implementations provide their own mechanisms to start
application in the form of the mpirun command.

One of the most important factors when running large MPI jobs is
mapping of the MPI ranks to compute nodes, and binding (or
pinning) them to CPU cores. Neglecting to do that, or doing that in
an suboptimal way can severely affect performance. In this regard
there are some differences when it comes to running applications
compiled against the two supported MPI environments.

Also note that the choice of MPI should be based on which MPI the
code is compiled with support for. So if module list give you a
OpenMPI/-reading, you should focus on the OpenMPI part beneath, if
given a impi/-reading focus on the Intel MPI part

OpenMPI

On systems with Mellanox InfiniBand, OpenMPI is the implementation
recommended by Mellanox due to it's support for the HPCX
communication
libraries.

srun

With OpenMPI, srun is the preferred way to start MPI programs due to
good integration with the Slurm scheduler environment:

srun /path/to/MySoftWare_exec

Executed as above, srun uses Slurm's default binding and mapping
algorithms (currently --cpu_bind=cores), which can be
changed using either
command-line parameters, or environment variables. Parameters specific
to OpenMPI can be set using environment
variables.

In the above scenario srun uses the PMI2 interface to launch the MPI
ranks on the compute nodes, and to exchange the InfiniBand address information between
the ranks. For large jobs the startup might be faster using OpenMPI's PMIx method:

srun --mpi=pmix /path/to/MySoftWare_exec

The startup time might be improved further using the OpenMPI MCA
pmix_base_async_modex argument (see below). With srun this needs to be
set using an environment variable.

mpirun

For those familiar with the OpenMPI tools, MPI applications can also
be started using the mpirun command:

mpirun /path/to/MySoftWare_exec

By default, mpirun binds ranks to cores, and maps them by
socket. Please refer to the
documentation
if you need to change those settings. Note that -report-bindings is
a very useful option if you want to inspect the individual MPI ranks
to see on which nodes, and on which CPU cores they run.

When launching large jobs with sparse communication patterns
(neighbor to neighbor, local communication) the startup time will be improved
by using the following command line argument:

mpirun -mca pmix_base_async_modex 1 ...

In the method above the address information will be exchanged between the ranks on a
need-to-know basis, i.e., at first data exchange between two ranks, instead of an all to all communication
step at program startup. Applications with dense communication patterns (peer to peer exchanges
with all ranks) will likely experience a slowdown.

Intel MPI

mpirun

At this moment, for performance reasons mpirun is the preferred way
to start applications that use Intel MPI:

srun

With srun, Intel MPI applications can be started as follows:

srun /path/to/MySoftWare_exec

We have observed that in the current setup some applications compiled
against Intel MPI and executed with srun achieve inferior
performance compared to the same code executed with mpirun. Until
this is resolved, we suggest using mpirun to start applications.

Final remarks

Note that when executing mpirun from within a Slurm allocation there
is no need to provide neither the number of MPI ranks (-np), nor the
host file (-hostfile): those are obtained automatically by
mpirun. This is also be the case with srun.